Data mining of routine laboratory tests can predict liver disease progression in Egyptian diabetic patients with hepatitis C virus (G4) infection: a cohort study of 71 806 patients

Data mining of routine laboratory tests can predict liver disease progression in Egyptian... ObjectivesHepatitis C virus (HCV) and diabetes mellitus (DM) are prevalent diseases worldwide, associated with significant morbidity, mortality, and mutual association. The aims of this study were as follows: (i) find the prevalence of DM among 71 806 Egyptian patients with chronic HCV infection and its effect on liver disease progression and (ii) using data mining of routine tests to predict hepatic fibrosis in diabetic patients with HCV infection.Patients and methodsA retrospective multicentered study included laboratory and histopathological data of 71 806 patients with HCV infection collected by Egyptian National Committee for control of viral hepatitis. Using data mining analysis, we constructed decision tree algorithm to assess predictors of fibrosis progression in diabetic patients with HCV.ResultsOverall, 12 018 (16.8%) patients were diagnosed as having diabetes [6428: fasting blood glucose ≥126 mg/dl (9%) and 5590: fasting blood glucose ≥110–126 mg/dl (7.8%)]. DM was significantly associated with advanced age, high BMI and α-fetoprotein (AFP), and low platelets and serum albumin (P≤0.001). Advanced liver fibrosis (F3–F4) was significantly correlated with DM (P≤0.001) irrespective of age. Of 16 attributes, decision tree model for fibrosis showed AFP was most decisive with cutoff of 5.25 ng/ml as starting point of fibrosis. AFP level greater than cutoff in patients was the first important splitting attribute; age and platelet count were second important splitting attributes.Conclusion(i) Chronic HCV is significantly associated with DM (16.8%). (ii) Advanced age, high BMI and AFP, low platelets count and albumin show significant association with DM in HCV. (iii) AFP cutoff of 5.25 is a starting point of fibrosis development and integrated into mathematical model to predict development of liver fibrosis in diabetics with HCV (G4) infection. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Journal of Gastroenterology & Hepatology Wolters Kluwer Health

Data mining of routine laboratory tests can predict liver disease progression in Egyptian diabetic patients with hepatitis C virus (G4) infection: a cohort study of 71 806 patients

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Publisher
Wolters Kluwer
Copyright
Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.
ISSN
0954-691X
eISSN
1473-5687
D.O.I.
10.1097/MEG.0000000000001008
Publisher site
See Article on Publisher Site

Abstract

ObjectivesHepatitis C virus (HCV) and diabetes mellitus (DM) are prevalent diseases worldwide, associated with significant morbidity, mortality, and mutual association. The aims of this study were as follows: (i) find the prevalence of DM among 71 806 Egyptian patients with chronic HCV infection and its effect on liver disease progression and (ii) using data mining of routine tests to predict hepatic fibrosis in diabetic patients with HCV infection.Patients and methodsA retrospective multicentered study included laboratory and histopathological data of 71 806 patients with HCV infection collected by Egyptian National Committee for control of viral hepatitis. Using data mining analysis, we constructed decision tree algorithm to assess predictors of fibrosis progression in diabetic patients with HCV.ResultsOverall, 12 018 (16.8%) patients were diagnosed as having diabetes [6428: fasting blood glucose ≥126 mg/dl (9%) and 5590: fasting blood glucose ≥110–126 mg/dl (7.8%)]. DM was significantly associated with advanced age, high BMI and α-fetoprotein (AFP), and low platelets and serum albumin (P≤0.001). Advanced liver fibrosis (F3–F4) was significantly correlated with DM (P≤0.001) irrespective of age. Of 16 attributes, decision tree model for fibrosis showed AFP was most decisive with cutoff of 5.25 ng/ml as starting point of fibrosis. AFP level greater than cutoff in patients was the first important splitting attribute; age and platelet count were second important splitting attributes.Conclusion(i) Chronic HCV is significantly associated with DM (16.8%). (ii) Advanced age, high BMI and AFP, low platelets count and albumin show significant association with DM in HCV. (iii) AFP cutoff of 5.25 is a starting point of fibrosis development and integrated into mathematical model to predict development of liver fibrosis in diabetics with HCV (G4) infection.

Journal

European Journal of Gastroenterology & HepatologyWolters Kluwer Health

Published: Feb 1, 2018

References

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